Imprecise task scheduling and overload management using OR-ULD

J. Hansson, M. Thuresson, S. H. Son

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

This paper evaluates the OR-ULD (Overload Resolution using Utility Loss Density) algorithm for imprecise computation workloads, where tasks are decomposed into one mandatory task and one optional task. OR-ULD is a value-driven overload resolution algorithm running in O(n log n) time, where n is the number of tasks. The algorithm is invoked only in case of transient overloads. By representing error using value functions, we get a general model for representing quality tradeoffs. Our performance studies show that OR-ULD overall performs better than the MF (Mandatory First) algorithm in reducing the total error and the total weighted error. In addition, OR-ULD minimizes the number of discarded optional tasks. The approach provides the flexibility that enables multiple strategies to be used to resolve overloads, e.g., overloads may be resolved by replacing transactions with contingency transactions, and non-critical regular transactions may be dropped or postponed.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages307-314
Number of pages8
ISBN (Electronic)0769509304, 9780769509303
DOIs
StatePublished - 2000
Event7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000 - Cheju Island, Korea, Republic of
Duration: 12 Dec 200014 Dec 2000

Publication series

NameProceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000

Conference

Conference7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
Country/TerritoryKorea, Republic of
CityCheju Island
Period12/12/0014/12/00

Bibliographical note

Publisher Copyright:
© 2000 IEEE.

Keywords

  • Computational modeling
  • Computer networks
  • Computer science
  • Dynamic scheduling
  • Processor scheduling
  • Real time systems
  • Runtime
  • Signal processing algorithms
  • Signal resolution
  • Time factors

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